Which is more popular, Chat with your enterprise data using LLM or Graphify?

Graphify has more GitHub stars (123,420 vs 865).

Which is more actively developed, Chat with your enterprise data using LLM or Graphify?

Graphify had more commits in the last 90 days (1,056 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

Chat with your enterprise data using LLM has had no commit in 21 months; Graphify is actively maintained (1,056 commits in the last 90 days).
Graphify is growing faster: +6,540 GitHub stars in the last 30 days vs +-0 for Chat with your enterprise data using LLM.
Chat with your enterprise data using LLM is open-source; Graphify is freemium.
Pick Chat with your enterprise data using LLM for: open-source sample for chatting with uploaded enterprise data using Azure OpenAI and vector search. Pick Graphify for: local tool that parses code, docs, SQL schemas, configs, and PDFs into a queryable knowledge graph.

From GitHub data refreshed daily.

Open-source sample for chatting with uploaded enterprise data using Azure OpenAI and vector search

Local tool that parses code, docs, SQL schemas, configs, and PDFs into a queryable knowledge graph

	Chat with your enterprise data using LLM	Graphify
Stars	865	123.4k
Star velocity /mo	-0.4736842105263158	6.5k
Commits (90d)	0	1.1k
Releases (6m)	0	10
Overall score	0.12103260760690508	0.9044125608136018

+Supports multiple vector stores (Pinecone, Redis, Azure Cognitive Search) providing flexibility in deployment options
+Includes comprehensive evaluation framework with Prompt Flow integration and metrics like groundedness and Ada similarity
+Active development with regular updates and refactoring to improve core functionality and remove complexity

-Designed as a sample application rather than production-ready solution, requiring additional development for enterprise deployment
-Specifically tied to Azure OpenAI Service, limiting flexibility in LLM provider choice
-Has undergone multiple refactoring cycles that removed features, suggesting potential instability in feature set

•Enterprise document Q&A systems where employees need to query internal knowledge bases using natural language
•Internal chatbots for customer support teams to quickly access company policies and procedures
•Research and development teams building custom RAG applications for proprietary data analysis

Which is more popular, Chat with your enterprise data using LLM or Graphify?: Graphify has more GitHub stars (123,420 vs 865).
Which is more actively developed, Chat with your enterprise data using LLM or Graphify?: Graphify had more commits in the last 90 days (1,056 vs 0).
Should I use Chat with your enterprise data using LLM or Graphify?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.